No Arabic abstract
For a track based polarimeter, such as the Imaging X-ray Polarimetry Explorer (IXPE), the sensitivity to polarization depends on the modulation factor, which is a strong function of energy. In previous work, a likelihood method was developed that would account for this variation in order to estimate the minimum detectable polarization (MDP). That method essentially required that the position angles of individual events should be known precisely. In a separate work, however, it was shown that using a machine learning method for measuring event tracks can generate track angle uncertainties, which can be used in the analysis. Here, the maximum likelihood method is used as a basis for revising the estimate of the MDP in a general way that can include uncertainties in event track position angles. The resultant MDP depends solely upon the distribution of track angle uncertainties present in the input data. Due to the physics of the IXPE detectors, it is possible to derive a simple relationship between these angular uncertainties and the energy-dependent modulation function as a step in the process.
We present a statistical assessment of both, observed and reported, photometric uncertainties in the OGLE-IV Galactic bulge microlensing survey data. This dataset is widely used for the detection of variable stars, transient objects, discovery of microlensing events, and characterization of the exo-planetary systems. Large collections of RR Lyrae stars and Cepheids discovered by the OGLE project toward the Galactic bulge provide light curves based on this dataset. We describe the method of analysis, and provide the procedure, which can be used to update preliminary photometric uncertainties, provided with the light curves, to the ones reflecting the actual observed scatter at a given magnitude and for a given CCD detector of the OGLE-IV camera.This is of key importance for data modeling, in particular, for the correct estimation of the goodness of fit.
Dimensionality reduction and matrix factorization techniques are important and useful machine-learning techniques in many fields. Nonnegative matrix factorization (NMF) is particularly useful for spectral analysis and image processing in astronomy. I present the vectorized update rules and an independent proof of their convergence for NMF with heteroscedastic measurements and missing data. I release a Python implementation of the rules and use an optical spectroscopic dataset of extragalactic sources as an example for demonstration. A future paper will present results of applying the technique to image processing of planetary disks.
The angular differential imaging (ADI) is used to improve contrast in high resolution astronomical imaging. An example is the direct imaging of exoplanet in camera fed by Extreme Adaptive Optics. The subtraction of the main dazzling object to observe the faint companion was improved using Principal Component Analysis (PCA). It factorizes the positive astronomical frames into positive and negative components. On the contrary, the Nonnegative Matrix Factorization (NMF) uses only positive components, mimicking the actual composition of the long exposure images.
In the first half year of operation the satellite borne POLAR instrument detected a total of 55 Gamma-Ray Bursts about 10 of which were bright enough to allow for detailed polarization studies, thereby forming the start of the first Gamma-Ray Burst polarization catalog. In this paper a brief overview of the previous GRB polarization studies will be presented followed by an overview of the POLAR detector along with the first result of the in-flight performance. The detected Gamma-Ray bursts will be presented and finally prospects for polarization measurements of these events will be discussed.
The angular distribution of galaxies encodes a wealth of information about large scale structure. Ultimately, the Sloan Digital Sky Survey (SDSS) will record the angular positions of order 10^8 galaxies in five bands, adding significantly to the cosmological constraints. This is the first in a series of papers analyzing a rectangular stripe 2.5x90 degrees from early SDSS data. We present the angular correlation function for galaxies in four separate magnitude bins on angular scales ranging from 0.003 degrees to 15 degrees. Much of the focus of this paper is on potential systematic effects. We show that the final galaxy catalog -- with the mask accounting for regions of poor seeing, reddening, bright stars, etc. -- is free from external and internal systematic effects for galaxies brighter than r* = 22. Our estimator of the angular correlation function includes the effects of the integral constraint and the mask. The full covariance matrix of errors in these estimates is derived using mock catalogs with further estimates using a number of other methods.